1. Versioning AI Model Artifacts with OCI Object Storage

    Python

    Creating an OCI Object Storage bucket with versioning enabled is a cloud infrastructure task involving storage and data management. Versioning is a means of keeping multiple variants of an object in the same bucket, which can help you recover from both unintended user actions and application failures.

    In your case, if you're aiming to use versioned buckets to store AI model artifacts, you will benefit from having the ability to retrieve and manage various versions of your machine learning models. This could be particularly useful for maintaining model lineage, rolling back to previous model versions in case of issues, or audit purposes.

    To achieve this with Pulumi and Python, you would use the oci Pulumi provider. You need to create an oci.ObjectStorage.Bucket resource with the versioning attribute set to enable versioning.

    Here's the code to create an OCI Object Storage bucket with versioning:

    import pulumi import pulumi_oci as oci # Replace these variables with your own specific details compartment_id = 'your-compartment-oid' namespace = 'your-namespace' bucket_name = 'ai-model-artifacts-bucket' # Creating an OCI Object Storage bucket with versioning enabled. ai_model_bucket = oci.ObjectStorage.Bucket('aiModelArtifactsBucket', compartment_id=compartment_id, namespace=namespace, name=bucket_name, versioning='Enabled', # This line enables versioning on the bucket ) # Export the bucket's name and OCID (Oracle Cloud Identifier) pulumi.export('bucket_name', ai_model_bucket.name) pulumi.export('bucket_id', ai_model_bucket.id)

    This program first imports the required modules, pulumi and pulumi_oci. For the OCI provider, you must ensure that you have the necessary permissions and the compartment ID, namespace, and other config values are correct for your cloud environment. We set versioning to 'Enabled' to turn on versioning for the bucket.

    The pulumi.export lines at the end share the output of the program after deployment; in this case, the name and ID of the bucket. This information can be useful if you want to reference the bucket in other Pulumi stacks or in external tools.

    This Pulumi program would set up the infrastructure as code, which gives you the ability to track changes, replicate setups, and manage your infrastructure with version control systems like Git.

    Remember to replace 'your-compartment-oid', 'your-namespace', and 'ai-model-artifacts-bucket' with your specific Oracle Cloud Infrastructure (OCI) compartment ID, namespace, and a suitable name for your bucket respectively.

    Finally, run this Pulumi program in a directory with a Pulumi.yaml file that specifies oci as the appropriate Pulumi provider. To deploy this infrastructure, you'd execute pulumi up on the command line from the same directory as your Pulumi program. After reviewing the proposed changes, you can confirm them to provision the infrastructure on OCI.

    For more information on working with OCI Object Storage in Pulumi, you can check the official Pulumi documentation.


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